The define–measure–analyze–improve–control (DMAIC) approach is a five-strata approach, namely DMAIC. This approach is the scientific approach for reducing the deviations and improving the capability levels of the manufacturing processes. The present work elaborates on DMAIC approach applied in reducing the process variations of the stub-end-hole boring operation of the manufacture of cra...

The service industry has become increasingly important in our daily lives and global economies, and improving service quality will have a significant social and economical impact. The massive amount of data readily available provides us with opportunities to integrate advanced statistical methodologies with system knowledge to better model and control the quality of service systems. Monitoring ...

background : few studies have focused on syndromic data to determine levels of alarm thresholds to detection of meningitis outbreaks. the purpose of this study was to determine threshold levels of meningitis outbreak in hamadan province, west of iran . methods : data on both confirmed and suspected cases of meningitis (fever and neurological symptom) form 21 march 2010 to 20 march 2012 were use...

although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. identifying the real time of the process changes is known as change-point estimation problem. there are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. in this paper we propose a novel appro...

the most well-known uni-arribute control chart used to monitor the number of nonconformities per unit is the shewhart type c-chart. in this paper, a new method is proposed in an attempt to reduce the false alarm rate in the c-chart. to do this, the decision on beliefs (dob) concept is first uti [1] corresponding author e-mail: [email protected]   lized to design an iterat...

Multivariate statistical process control charts are often used for process monitoring to detect out-of-control anomalies. However, multivariate control charts based on conventional statistical distance measures, such as the one used in the Hotelling’s T 2 control chart, cannot scale up to large amounts of complex process data, e.g. data with a large number of variables and a high rate of data s...